Fast-Neutron Radiolysis of Sub- and Supercritical Water at 300–600 °C and 25 MPa: A Monte Carlo Track Chemistry Simulation Study
Bibliographic record
Abstract
(1) Background: Supercritical water-cooled reactors (SCWRs) and their smaller modular variants (SMRs) are part of the ‘Generation IV International Forum’ (GIF) on advanced nuclear energy systems. These reactors operate beyond the critical point of water (tc = 373.95 °C and Pc = 22.06 MPa), which introduces specific technical challenges that need to be addressed. The primary concerns involve the effects of intense radiation fields—including fast neutrons, recoil protons/oxygen ions, and γ rays—on the chemistry of the coolant fluid and the integrity of construction materials. (2) Methods: This study employs Monte Carlo simulations of radiation track chemistry to investigate the yields of radiolytic species in SCWRs/SMRs exposed to 2 MeV neutrons. In our calculations, only the contributions from the first three recoil protons with initial energies of 1.264, 0.465, and 0.171 MeV were considered. Our analysis was conducted at both subcritical (300 and 350 °C) and supercritical temperatures (400–600 °C), maintaining a constant pressure of 25 MPa. (3) Results: Our simulations provide insights into the radiolytic formation of chemical species such as e−aq, H●, H2, ●OH, and H2O2 from ~1 ps to 1 ms. Compared to data from radiation with low linear energy transfer (LET), the G(e−aq) and G(●OH) values obtained for fast neutrons show a similar temporal dependence but with smaller amplitude—a result demonstrating the high LET nature of fast neutrons. A notable outcome of our simulations is the marked increase in G(●OH) and G(H2), coupled with a corresponding reduction in G(H●), observed during the homogeneous chemical stage of radiolysis. This evolution is attributed to the oxidation of water by the H● atom according to the reaction H● + H2O → ●OH + H2. This reaction acts as a significant source of H2, potentially reducing the need to add extra hydrogen to the reactor’s coolant water to suppress the net radiolytic production of oxidizing species. Unlike in subcritical water, our simulations also indicate that G(H2O2) remains very low in low-density SCW throughout the interval from ~1 ps to 1 ms, suggesting that H2O2 is less likely to contribute to oxidative stress under these conditions. (4) Conclusions: The results of this study could significantly impact water-chemistry management in the proposed SCWRs and SCW-SMRs, which is crucial for assessing and mitigating the corrosion risks to reactor materials, especially for long-term operation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".